
"""simple docstring"""



import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier


def lowerCamelCase_				(     _lowerCamelCase			:	Tuple				):
       return (data["data"], data["target"])


def lowerCamelCase_				(     _lowerCamelCase			:	Optional[int]					,				_lowerCamelCase			:	Any				):
       lowerCamelCase_       							=		XGBClassifier()
       classifier.fit(snake_case__					,				snake_case__				)
       return classifier


def lowerCamelCase_				(     ):
       lowerCamelCase_       							=		load_iris()
       lowerCamelCase_							,							lowerCamelCase_       							=		data_handling(snake_case__				)
       lowerCamelCase_							,							lowerCamelCase_							,							lowerCamelCase_							,							lowerCamelCase_       							=		train_test_split(
           snake_case__					,				snake_case__					,				test_size=0.25				)

       lowerCamelCase_       							=		iris['''target_names''']

       # Create an XGBoost Classifier from the training data
       lowerCamelCase_       							=		xgboost(snake_case__					,				snake_case__				)

       # Display the confusion matrix of the classifier with both training and test sets
       ConfusionMatrixDisplay.from_estimator(
           snake_case__					,				snake_case__					,				snake_case__					,				display_labels=snake_case__					,				cmap='''Blues'''					,				normalize='''true'''					,				)
       plt.title('''Normalized Confusion Matrix - IRIS Dataset'''				)
       plt.show()


if __name__ == "__main__":
 import doctest

 doctest.testmod(verbose=True)
 main()





"""simple docstring"""




def        a__					(							snake_case__							)		->   list:

			if len(snake_case__							) <= 1:
						return [tuple(snake_case__							)]

			lowerCamelCase      =   []

			def generate(snake_case__			,					snake_case__							):
						lowerCamelCase      =   [0] * n
						res.append(tuple(snake_case__							)							)

						lowerCamelCase      =   0
						while i < n:
									if c[i] < i:
												if i % 2 == 0:
															lowerCamelCase ,  lowerCamelCase      =   arr[i], arr[0]
												else:
															lowerCamelCase ,  lowerCamelCase      =   arr[i], arr[c[i]]
												res.append(tuple(snake_case__							)							)
												c[i] += 1
												lowerCamelCase      =   0
									else:
												lowerCamelCase      =   0
												i += 1

			generate(len(snake_case__							)			,					snake_case__							)
			return res


if __name__ == "__main__":
					lowerCAmelCase				:     str					=				input("""Enter numbers separated by a comma:\n""").strip()
					lowerCAmelCase				:     List[Any]					=				[int(item) for item in user_input.split(""",""")]
					print(heaps(arr))



